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BC linkfox-jiimore-get-niche-info

查询并分析极目数据的亚马逊细分市场洞察，包括市场指标、买家评论、竞争格局、价格走势和增长趋势。当用户提到细分市场分析、市场洞察、细分市场数据、市场竞争分析、品牌集中度、新品上架成功率、断货率、价格趋势、评论洞察、市场需求评分、niche market insights, market metrics, competition analysis, price trends, growth trends, Jiimore data, market intelligence, out-of-stock rate时触发此技能。即使用户未明确提及"极目"或"细分市场"，只要其需求涉及通过市场ID查询特定亚马逊细分市场的市场级情报，也应触发此技能。

ClawHub Agent Skills author: linkfox-ai v1.0.6 MIT-0 6 files body ≈ 1 930 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

查询并分析极目数据的亚马逊细分市场洞察，包括市场指标、买家评论、竞争格局、价格走势和增长趋势。当用户提到细分市场分析、市场洞察、细分市场数据、市场竞争分析、品牌集中度、新品上架成功率、断货率、价格趋势、评论洞察、市场需求评分、niche market insights, market metrics…

As a process C 52/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerData and analyticsSoftware developmentMarketingtype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
84/100
safety, quality, tests
Safety 60%
92
Quality 40%
73
Run on models
none yet
Process rating
C
52/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 8

✓ No critical or high findings

Medium and low: 8
  • low Secrets in code secret-high-entropy-token references/api.md:59
    High-entropy token-like string (may be an id, hash or a credential)
    | sell…ore | integer | 销售伙伴数量(90天前) |
  • low Secrets in code secret-high-entropy-token references/api.md:60
    High-entropy token-like string (may be an id, hash or a credential)
    | sell…ore | integer | 销售伙伴数量(360天前) |
  • low Secrets in code secret-high-entropy-token references/api.md:62
    High-entropy token-like string (may be an id, hash or a credential)
    | sell…ore | integer | 销售伙伴数量(360 天统计)(90天前) |
  • low Secrets in code secret-high-entropy-token references/api.md:63
    High-entropy token-like string (may be an id, hash or a credential)
    | sell…ore | integer | 销售伙伴数量(360 天统计)(360天前) |
  • low Secrets in code secret-high-entropy-token references/api.md:99
    High-entropy token-like string (may be an id, hash or a credential)
    | top5…ore | number | 前5个商品所占细分市场的点击量份额(90天前) |
  • low Dangerous commands cmd-shell-rc references/onboarding.md:13
    Writes to a shell startup file (quoted — discussed, not commanded)
    - macOS zsh：`echo 'export LINKFOX_AGENT_API_KEY="<key>"' >> ~/.zshrc && source ~/.zshrc`
    quoted
  • low Dangerous commands cmd-shell-rc references/onboarding.md:14
    Writes to a shell startup file (detector / deny-list definition)
    - Linux bash：`echo 'export LINKFOX_AGENT_API_KEY="<key>"' >> ~/.bashrc && source ~/.bashrc`
    detector
  • low Secrets in code secret-high-entropy-token scripts/onboarding.py:49
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    or "eyJh…iJ9")
    quoted

Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 52/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 55Failures and branches. 1 branches
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 59 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1930 tokens
  • 100Running it twice. No mutating operations
  • low 10 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (7 tags): a typed call is more reliable

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -31 of 2 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 322: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 59 items
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: suspicious
The skill is a real market-data tool, but it also handles account login, API-key creation, billing orders, payment QR codes, and persistent local storage in ways users should review carefully.
LLM: suspicious (high) · 14 Aug 2026